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Compute-and-forward for discrete memoryless networks

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Rateless Codes for AVC Models

Michael Christoph Gastpar

The arbitrarily varying channel (AVC) is a channel model whose state is selected maliciously by an adversary. Fixed-blocklength coding assumes a worst-case bound on the adversary's capabilities, which leads to pessimistic results. This paper defines a vari ...

2010

Linear Universal Decoder for Compound Discrete Memoryless Channels

Rethnakaran Pulikkoonattu

Shannon in his seminal work \cite{paper:shannon} formalized the framework on the problem of digital communication of information and storage. He quantified the fundamental limits of compression and transmission rates. The quantity \textit{channel capacity} ...

2009

Concentration of Magnetization for Linear Block Codes

Nicolas Macris, Satish Babu Korada, Shrinivas Kudekar

We consider communication over the binary erasure and the binary additive white gaussian noise channels using fixed linear block codes and also appropriate ensembles of such codes. We show concentration of the magnetization over the channel realizations an ...

2008

On communication over discrete memoryless channels with noiseless feedback

Peter Allan Berlin

The addition of a feedback link to a discrete memoryless channel does not increase its capacity, but it does bring with it other benefits. One of these benefits is an increase to the best achievable error exponent. In the first part of this thesis we revis ...

EPFL2008

On capacity of line networks

Christina Fragouli, Daniela Tuninetti, Urs Niesen

We consider communication through a cascade of discrete memoryless channels (DMCs). The source and destination node of this cascade are allowed to use coding schemes of arbi- trary complexity, but the intermediate relay nodes are restricted to process only ...

Institute of Electrical and Electronics Engineers2007

Randomization bounds on Gaussian arbitrarily varying channels

Michael Christoph Gastpar

The random coding capacity of the Gaussian arbitrarily varying channel (GAVC) under a maximal probability of error criterion is equal to that of an additive white Gaussian noise (AWGN) channel with the interference power as additional noise. The determinis ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2006

On the capacity of multiple input erasure relay channels: The Non-degraded case

Ramin Khalili

We consider in this paper a network that consists of two senders and two receivers. We further assume that each sender could act as a relay for other communications. All channels connecting these nodes are supposed to be erasure channels where symbols are ...

2005

Joint source-channel coding with feedback

Communications is about conveying information from one point to another subject to certain performance constraints. The information is assumed to be generated by a source and may, for example, represent a voice waveform, the reading of a thermal sensor, or ...

EPFL2005

On the capacity of erasure relay channel: Multi-relay case

Ramin Khalili

We consider here a single sender-destination multirelay channel. The links connecting the nodes are supposed to be erasure where symbols are received correctly without any error, or lost. We consider that the nodes are not able to use any interference canc ...

2005

To code or not to code: lossy source-channel communication revisited

Martin Vetterli, Michael Christoph Gastpar, Bixio Rimoldi

What makes a source–channel communication system optimal? It is shown that in order to achieve an optimal cost–distortion tradeoff, the source and the channel have to be matched in a probabilistic sense. The match (or lack of it) involves the source distri ...

2003